We illustrate the benefits of PromptGen with several experiments.
Figure REF  demonstrates our main findings with StyleGAN2 trained on FFHQ [1]} without any labels, while we also show results for StyleNeRF [2]}, diffusion autoencoder [3]}, and NVAE [4]} in Section .
Figure REF (a) illustrates how we can sample from StyleGAN2 based on text descriptions such as “a photo of a baby”.
Figure REF (b) shows that PromptGen can leverage a race classifier (potentially trained on a different dataset) to sample uniformly across all races, de-biasing the pre-trained StyleGAN2.
Figure REF (d) illustrates that PromptGen can generate images of the same identity in different poses, guided by a pose regressor.
